Upright and inverted unfamiliar face-matching tasks – everything correlates everywhere all at once

In a key study, Megreya and Burton (Memory & Cognition, 34, 865–876, 2006) argued that identity-matching tasks using unfamiliar faces may not effectively measure general ‘real-world’ face-processing ability – that is they are “not faces”. They observed a high correlation in performance between upright and inverted unfamiliar face matching, a pattern not seen with familiar faces, which they interpreted as indicating unfamiliar face matching is qualitatively different and largely driven by image-specific factors. However, the authors cautioned that this limitation likely applies only to unfamiliar face-matching tasks for identity rather than other types of face judgements (e.g., emotion). The present study replicates and extends these findings by considering within-subject performance for upright/inverted unfamiliar face matching across various paradigms (sequential/simultaneous presentation or sorting) and face-judgement types (identity or emotion), whilst considering different types of measures (accuracy and reaction time). Our results illustrated high correlations for upright/inverted conditions were universally observed within tasks for both accuracy and reaction times. Subsequent factor analyses indicated that upright and inverted conditions loaded together into task-specific latent variables. These results concur with the conclusions of Megreya and Burton (2006) and extend to both identity and emotion matching tasks – that is such tasks exhibit low construct validity for testing hypotheses about much general ‘everyday’ face processing. We propose that researchers should carefully consider alignment between their test materials and the theoretical ‘constructs’ they aim to measure, ensuring more accurate and meaningful interpretations of their results

Increased Intermembrane Space [Ca2+] Drives Mitochondrial Structural Damage in CPVT

BACKGROUND:Mitochondrial dysfunction caused by abnormally high RyR2 (ryanodine receptor) activity is a common finding in cardiovascular diseases. Mechanisms linking RyR2 gain of function with mitochondrial remodeling remain elusive. We hypothesized that RyR2 hyperactivity in cardiac disease increases [Ca2+] in the mitochondrial intermembrane space (IMS) and activates the Ca2+-sensitive protease calpain, driving remodeling of mitochondrial cristae architecture through cleavage of structural protein OPA1 (optic atrophy protein 1).METHODS:We generated a highly arrhythmogenic rat model of catecholaminergic polymorphic ventricular tachycardia, induced by RyR2 gain-of-function mutation S2236L(±). We created a new biosensor to measure IMS-[Ca2+] in adult cardiomyocytes with intact Ca2+ cycling. We used ex vivo whole heart optical mapping, confocal and electron microscopy, as well as in vivo/in vitro gene editing techniques to test the effects of calpain in the IMS.RESULTS:We found altered mitochondrial cristae structure, increased IMS-[Ca2+], reduced OPA1 expression, and augmented mito-reactive oxygen species emission in catecholaminergic polymorphic ventricular tachycardia myocytes. We show that calpain-mediated OPA1 cleavage led to disrupted cristae organization and, thereby, decreased electron transport chain supercomplex assembly, resulting in accelerated reactive oxygen species production. Genetic inhibition of calpain activity in IMS reversed mitochondria structural defects in catecholaminergic polymorphic ventricular tachycardia myocytes and reduced arrhythmic burden in ex vivo optically mapped hearts.CONCLUSIONS:Our data suggest that RyR2 hyperactivity contributes to mitochondrial structural damage by promoting an increase in IMS-[Ca2+], sufficient to activate IMS-residing calpain. Calpain activation leads to proteolysis of OPA1 and cristae widening, thereby decreasing assembly of electron transport chain components into supercomplexes. Consequently, excessive mito-reactive oxygen species release critically contributes to RyR2 hyperactivation and ventricular tachyarrhythmia. Our new findings suggest that targeting IMS calpain may be beneficial in patients at risk for sudden cardiac death

The currency of Trump's techno-authoritarian populism

The speed at which the cryptocurrency sector has become entangled with the new Trump administration is astonishing. As journalists have pointed out, the degree of conflict of interest(s) - if not self-evident graft - in the Trump family's crypto dealings is unprecedented in the U.S. This commentary explores the ways Trump and his family lean into a mixture of techno-libertarian and authoritarian-populist rhetoric, along with a celebration of financial innovation, to mask what appears to be an effort to enrich their family and friends, which now includes a network of Silicon Valley investors

The development of Liver Research Cymru, a new partnership to increase hepatology research activity in Wales

BackgroundThe incidence and severity of liver disease in the United Kingdom have increased over the last 20 years. Many patients present with advanced disease with limited treatment options and subsequently high morbidity and mortality. There was also a significant correlation with deprivation. Strategies that support the earlier detection of liver disease are paramount to reverse this trend. Despite significant progress in terms of novel pathways, the optimal strategy for early detection of liver disease remains unknown. Novel ways to tackle the deprivation gradient and reduce health inequalities are urgently required.MethodsClinical research has an enormous role to play both in terms of identifying the true scale of this challenge, where current gaps exist, and to identify the optimal early detection strategies and their implementation. We therefore established Liver Research Cymru (LRC) a multi-disciplinary collaboration that seeks to maximise the benefits from our existing data sources and clinical networks and increase the output of hepatology research in Wales.ResultsLRC has developed the first Wales wide research collaborative. We have successfully collaborated with the Secure Anonymised Information Linkage (SAIL) data resource to develop a greater understanding of liver disease burdens through comprehensive analysis of primary and secondary care data. We are now using this information to evaluate the effectiveness of local early detection pathways and to identify the scale of delays in diagnosis with a view to addressing this important care gap.ConclusionLRC has successfully brought together patients. Hepatologists and population/primary care academics to better understand current discrepancies in the early diagnosis of liver disease in Wales. In addition, it has laid a foundation for future research work based both on our preliminary findings and allowed us to collaborate with other more established liver disease research groups

Multi-Scale Analysis of Reinforced Composites

The thesis centres on multi-scale modelling of heterogeneous solids, where the macroscopic behaviour is intricately linked to the microscopic structure. To manage the substantial memory and computational power demands of multi-scale modelling, a discrete Representative Volume Element (RVE) boundary approach based on a finite element model of the microstructure is employed. RVE refers to a small unit of a material that represents the whole material in terms of structure and properties. A new homogenisation method is explored in this research, and subsequently, the results obtained from this approach are rigorously compared to analytical methods using multiple verifying examples. This comparative analysis provides insights into the accuracy and reliability of the multi-scale modelling technique in predicting material behaviours across different scales.Homogenous, isotropic and transversely isotropic 3D solids are investigated. Then, a homogenisation tool employing the least squares method is used to determine the effective elastic properties of the composite. A more advanced tool, a Neural Network, utilises data from the least squares method to predict the elastic properties of the composite without the necessity of re-modelling the RVE and conducting additional tests.The trained neural network, which utilises data derived from least squared method plays a crucial role in predicting elastic properties of composites with very high accuracy. By integrating the neural network’s predictions with an optimisation algorithm, they can effectively tailor materials to meet specific criteria such as cost-efficiency and lightweight construction. This integrated approach not only enhances design precision but also reduces the need for extensive re-modelling of the RVE and repetitive testing. Ultimately, it fosters the development of innovative materials that strike an optimal balance between performance and resource utilisation in various engineering applications

Recognizing the natural heritage of landscape in the law of England and Wales

Natural heritage is a term that is little used in the context of environmental law, but it is essential in understanding the connections between people, nature and landscape. Protecting the natural heritage of landscape, recognizing the spatial and temporal connections between people and place, will be crucial in addressing the nature crisis. Law can provide an important means of reflecting those values and this article sets out three ways in which the law in England and Wales should be reformed to this end. First, heritage law needs revising to include the protection of tangible natural heritage features in the landscape, alongside built cultural heritage. Secondly, planning law needs to clearly articulate the more intangible values of the natural heritage in landscape for land use. Thirdly, these values and features of natural heritage in the landscape need to be protected in rules and standards (legal or otherwise) that govern management practices in a rural context, ie, in the spheres of agriculture, forestry and inland waterways